Customized Category Based Clustering of URLs

Abstract

Web applications are taking popularity in number of ways. Monitoring the client side data allow for gathering valuable information about its behaviour. In this paper an intelligent and integrated system for user activity monitoring for both computer and internet movement is proposed. The system provides on-line and off-line monitoring and allows detecting user behaviour. On-line monitoring is carried in real time and is used to predict user actions. Off-line monitoring is carried out after user has ended his work, and is based on the analysis of statistical parameters of user behaviour. A method for the identifying the category of web sites is also presented. Our system performs clustering on the basis of URL. The URL clustering is very informative, making techniques based on it faster than that make use of text information as well.